Online retailers are always looking to differentiate themselves in more meaningful ways. Compelling shopping experiences, product recommendations, and overall superior customer service are key ways retailers set themselves apart. Today's data-driven marketing tools can help them unlock those experiences by using the data they have about their customers.
Prior to founding my own company, I served as the director of analytics on the 2008 Obama campaign. By experimenting with changes to elements of the campaign splash page, we were able to help raise an additional $57 million in campaign donations.
The guiding principles that made the campaign successful are no different from approaches online retailers and other marketers can adopt to make a real business impact.
First, you need to know your constituent. The behavior of visitors who come to your website is very much indicative of the kind of messaging that would work on them. What you show a returning visitor is different from what you'd show to a new visitor, or a mobile visitor vs. a desktop visitor.
The urgency for businesses to use data to show the right thing, to the right person, at the right time is stronger than ever. Targeted messaging is the most to effective way to get consumers to convert.
Second, you must know the facts. One of the greatest challenges (and areas for error) for businesses is getting the data right. Online retailers should take prudent effort to make sure the infrastructure and process they've implemented is sound. For example, the "novelty effect" suggests that just because a change has an impact initially doesn't mean it can be sustained over time. Will your customers grow tired of cyber deals every 10 minutes for a week?
Finally, it's imperative to ask the right questions. The challenge for online retailers is not about prescribing the right answers but about asking the right questions. For instance, are you trying to see whether a visitor will respond better to more product selections on a page, or fewer? Consider first what you want the answers to be, and those hypotheses will then help you decide what to measure.
Common examples of A/B testing for online retail include homepage bounce rates, category-page views, product-page views, shopping cart ads, and all stages in a checkout flow all the way to the Thank You page.
Take the first step (it's free).
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